Nutrient and dissolved inorganic carbon variability in the North Pacific
Bibliographic record
Abstract
Abstract A compilation of surface water nutrient (phosphate, nitrate, and silicate) and partial pressure of CO2 (pCO2) observations from 1961 to 2016 reveals seasonal and interannual variability in the North Pacific. Nutrients and calculated dissolved inorganic carbon (DIC) reach maximum concentrations in March and minimum in August. Nutrient and DIC variability is in-phase (anti-phase) with changes in the mixed layer depth (sea surface temperature) north of 30 °N, and it is anti-phase (in-phase) with changes in Chl-a north of 40 °N (in 30 °N–40 °N). Seasonal drawdown of nutrients and DIC is larger toward the northwest and shows a local maximum in the boundary region between the subarctic and subtropics. Stoichiometric ratios of seasonal drawdown show that, compared to nitrate, silicate drawdown is large in the northwestern subarctic including the Bering and Okhotsk seas, and drawdown of carbon is larger toward the south. Net community production in mixed layer from March to July is estimated to be more than 6 gC/m2/mo in the boundary region between the subarctic and subtropics, the western subarctic, the Gulf of Alaska, and the Bering Sea. Nutrient and DIC concentrations vary with the Pacific Decadal Oscillation and the North Pacific Gyre Oscillation which cause changes in horizontal advection and vertical mixing. The DIC trend is positive in all analysis area and large in the western subtropics (> 1.0 μmol/l/yr). Averaged over the analysis area, it is increasing by 0.77 ± 0.03 μmol/l/yr (0.75 ± 0.02 μmol/kg/yr).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".